{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T03:56:36Z","timestamp":1768449396629,"version":"3.49.0"},"reference-count":49,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T00:00:00Z","timestamp":1735171200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Epidemiol. Infect."],"published-print":{"date-parts":[[2025]]},"abstract":"<jats:title>Abstract<\/jats:title>\n\t  <jats:p>The course of COVID-19 is highly variable, with genetics playing a significant role. Through large-scale genetic association studies, a link between single nucleotide polymorphisms and disease susceptibility and severity was established. However, individual single nucleotide polymorphisms identified thus far have shown modest effects, indicating a polygenic nature of this trait, and individually have limited predictive performance. To address this limitation, we investigated the performance of a polygenic risk score model in the context of COVID-19 severity in a Russian population. A genome-wide polygenic risk score model including information from over a million common single nucleotide polymorphisms was developed using summary statistics from the COVID-19 Host Genetics Initiative consortium. Low-coverage sequencing (5x) was performed for ~1000 participants, and polygenic risk score values were calculated for each individual. A multivariate logistic regression model was used to analyse the association between polygenic risk score and COVID-19 outcomes. We found that individuals in the top 10% of the polygenic risk score distribution had a markedly elevated risk of severe COVID-19, with adjusted odds ratio of 2.9 (95% confidence interval: 1.8\u20134.6, <jats:italic>p<\/jats:italic>-value = 4e-06), and more than four times higher risk of mortality from COVID-19 (adjusted odds ratio = 4.3, <jats:italic>p<\/jats:italic>-value = 2e-05). This study highlights the potential of polygenic risk score as a valuable tool for identifying individuals at increased risk of severe COVID-19 based on their genetic profile.<\/jats:p>","DOI":"10.1017\/s0950268824001778","type":"journal-article","created":{"date-parts":[[2024,12,25]],"date-time":"2024-12-25T22:05:22Z","timestamp":1735164322000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":1,"title":["Case\u2013control association study between polygenic risk score and COVID-19 severity in a Russian population using low-pass genome sequencing"],"prefix":"10.1017","volume":"153","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9291-7550","authenticated-orcid":false,"given":"Arina","family":"Nostaeva","sequence":"first","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valentin","family":"Shimansky","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Svetlana","family":"Apalko","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Kuznetsov","sequence":"additional","affiliation":[{"name":"Skolkovo Institute of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalya","family":"Sushentseva","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oleg","family":"Popov","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna","family":"Asinovskaya","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergei","family":"Mosenko","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lennart","family":"Karssen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrey","family":"Sarana","sequence":"additional","affiliation":[{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yurii","family":"Aulchenko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergey","family":"Shcherbak","sequence":"additional","affiliation":[{"name":"St. Petersburg State Budgetary Healthcare Institution"},{"name":"St. Petersburg State University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2024,12,26]]},"reference":[{"key":"S0950268824001778_r26","unstructured":"[26] Andrews, S (2010) FastQC: A Quality Control Tool for High Throughput Sequence Data. http:\/\/www.bioinformatics.babraham.ac.uk\/projects\/fastqc\/ (accessed 2010)."},{"key":"S0950268824001778_r32","unstructured":"[32] HapMap Project. 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